Search results for: academic performance index

Authors: Domenico Carmelo Mongelli

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The context of this research is that of the Italian reality, which, in order to adapt to the EU Directives that prohibit the production of internal combustion engines in favor of electric mobility from 2035, is extremely concerned about the significant loss of jobs resulting from the difficulty of the automotive industry in converting in such a short time and due to the reticence of potential buyers in the face of such an epochal change. The aim of the research is to evaluate for Italy the potential of the most valid alternative to this transition to electric: leaving the current production of diesel engines unchanged, no longer powered by gasoil, imported and responsible for greenhouse gas emissions, but powered entirely by a nationally produced and eco-sustainable fuel such as biodiesel. Today in Italy, the percentage of biodiesel mixed with gasoil for diesel engines is too low (around 10%); for this reason, this research aims to evaluate the functioning of current diesel engines powered 100% by biodiesel and the ability of the Italian production system to cope to this hypothesis. The research geographically identifies those abandoned lands in Italy, now out of the food market, which is best suited to an energy crop for the final production of biodiesel. The cultivation of oilseeds is identified, which for the Italian agro-industrial reality allows maximizing the agricultural and industrial yields of the transformation of the agricultural product into a final energy product and minimizing the production costs of the entire agro-industrial chain. To achieve this objective, specific databases are used, and energy and economic balances are prepared for the different agricultural product alternatives. Solutions are proposed and tested that allow the optimization of all production phases in both the agronomic and industrial phases. The biodiesel obtained from the most feasible of the alternatives examined is analyzed, and its compatibility with current diesel engines is identified, and from the evaluation of its thermo-fluid-dynamic properties, the engineering measures that allow the perfect functioning of current internal combustion engines are examined. The results deriving from experimental tests on the engine bench are evaluated to evaluate the performance of different engines fueled with biodiesel alone in terms of power, torque, specific consumption and useful thermal efficiency and compared with the performance of engines fueled with the current mixture of fuel on the market. The results deriving from experimental tests on the engine bench are evaluated to evaluate the polluting emissions of engines powered only by biodiesel and compared with current emissions. At this point, we proceed with the simulation of the total replacement of gasoil with biodiesel as a fuel for the current fleet of diesel vehicles in Italy, drawing the necessary conclusions in technological, energy, economic, and environmental terms and in terms of social and employment implications. The results allow us to evaluate the potential advantage of a total replacement of diesel fuel with biodiesel for powering road vehicles with diesel cycle internal combustion engines without significant changes to the current vehicle fleet and without requiring future changes to the automotive industry.

Keywords: biodiesel, economy, engines, environment

Procedia PDF Downloads 54

Authors: Obokhai Kess Asikhia

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This work explores design concept generation by understanding user needs through observation and interview. The aim is to examine several principles and guidelines in obtaining evidence from observing how users interact with the targeted product and interviewing them to acquire deep insights of their needs. With the help of Quality Function Deployment (QFD), the identified needs of the users while interacting with the product were ranked using the normalised weighting approach. Furthermore, a low fidelity prototype of the alarm clock is developed with a view of addressing the identified needs of the users. Finally, the low fidelity prototype design was evaluated with two design prototypes already existing in the market through a study involving 30 participants. Preliminary results reveal higher performance ratings by the majority of the participants of the new prototype compared to the other existing alarm clocks in the market used in the study.

Keywords: design concept, low fidelity prototype, normalised weighting approach, quality function deployment, user needs

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Authors: Sumonthip Kongtun Janphuk

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Ten cereal grains that usually used as ingredients in healthy products were studied for phytosteryl glucoside contents. β-sitosteryl glucoside in 10 cereal grains, including Phasecolus vulgaris L. (kidney bean), Sorghum bicolor (sorghum), Moringa oleifera Lam. (drumstick), Nelumbo nucifera (lotus), Vigna radiate L. (mung bean), Coix lacrymajobi (job’tears), Oryza sativa. (red rice), Glycine max L. Merrill. (soybean),Cucurbita maschata Decne (pumpkin) and Helianthas annuus (sunflower seeds), were analyzed using Thin-layer chromatography (TLC) and High-Performance liquid chromatography (HPLC). All grains were extracted with methanol before analysis. Red bean showed the maximum phytosteryl glucoside content of 0.42% w/w. The content of others were as follows: pumpkin seed 0.173%, mung bean 0.099 %, soybean 0.07%, dried moringa seed 0.067%, lotus seed 0.044%, sorghum 0.032%, sunflower seed 0.016%, Job's tears 0.012%, and brown rice 0.006%.

Keywords: cereal grains, phytosterol, β-sitosteryl glucoside, food analysis.

Procedia PDF Downloads 372

Authors: Komal Rathore, Kiesha Pierre, Kyle Cogswell, Aaron Driscoll, Andres Tejada Martinez, Gita Iranipour, Luke Mulford, Aydin Sunol

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Modeling of Biological Wastewater Treatment Plants requires several parameters for kinetic rate expressions, thermo-physical properties, and hydrodynamic behavior. The kinetics and associated mechanisms become complex due to several biological processes taking place in wastewater treatment plants at varying times and spatial scales. A dynamic process model that incorporated the complex model for activated sludge kinetics was developed using the BioWin software platform for an Advanced Wastewater Treatment Plant in Valrico, Florida. Due to the extensive number of tunable parameters, an experimental design was employed for judicious selection of the most influential parameter sets and their bounds. The model was tuned using both the influent and effluent plant data to reconcile and rectify the forecasted results from the BioWin Model. Amount of mixed liquor suspended solids in the oxidation ditch, aeration rates and recycle rates were adjusted accordingly. The experimental analysis and plant SCADA data were used to predict influent wastewater rates and composition profiles as a function of time for extended periods. The lumped dynamic model development process was coupled with Computational Fluid Dynamics (CFD) modeling of the key units such as oxidation ditches in the plant. Several CFD models that incorporate the nitrification-denitrification kinetics, as well as, hydrodynamics was developed and being tested using ANSYS Fluent software platform. These realistic and verified models developed using BioWin and ANSYS were used to plan beforehand the operating policies and control strategies for the biological wastewater plant accordingly that further allows regulatory compliance at minimum operational cost. These models, with a little bit of tuning, can be used for other biological wastewater treatment plants as well. The BioWin model mimics the existing performance of the Valrico Plant which allowed the operators and engineers to predict effluent behavior and take control actions to meet the discharge limits of the plant. Also, with the help of this model, we were able to find out the key kinetic and stoichiometric parameters which are significantly more important for modeling of biological wastewater treatment plants. One of the other important findings from this model were the effects of mixed liquor suspended solids and recycle ratios on the effluent concentration of various parameters such as total nitrogen, ammonia, nitrate, nitrite, etc. The ANSYS model allowed the abstraction of information such as the formation of dead zones increases through the length of the oxidation ditches as compared to near the aerators. These profiles were also very useful in studying the behavior of mixing patterns, effect of aerator speed, and use of baffles which in turn helps in optimizing the plant performance.

Keywords: computational fluid dynamics, flow-sheet simulation, kinetic modeling, process dynamics

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Authors: Shahbaz Amin, Sabir Hussain Shah, Sahib Khan

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This paper presents a thorough review concerning the design types of axial flux permanent magnet machines (AFPM) in terms of different features such as construction, design, materials, and manufacturing. Particular emphasis is given on the design and performance analysis of AFPM machines. A comparison among different permanent magnet machines is also provided. First of all, early and modern axial flux machines are mentioned. Secondly, rotor construction of different axial flux machines is described, then different stator constructions are mentioned depending upon the presence of slots and stator back iron. Then according to the arrangement of the rotor stator structure the machines are classified into single, double and multi-stack arrangements. Advantages, disadvantages and applications of each type of rotor and stator are pointed out. Finally on the basis of the reviewed literature merits, demerits, features and application of different axial flux machines structures are explained and clarified. Thus, this paper provides connection between the machines that are currently being used in industry and the developments of AFPM throughout the years.

Keywords: axial flux machines, axial flux applications, coreless machines, PM machines

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Authors: Benabdelaziz Soufyane

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The process of developing the activity of small and medium-sized enterprises(SME), and increasing the entrepreneurial sense, is becoming at the current period as one of the main bets, where many countries around the world try to give it the great importance because of their positive role in improving the economic development indicators in these countries. As a result of the sequential changes that international economic environment lives, the biggest global economic entities has become threatened because of different secretions financial crises and economic disorders. For this lots of countries tended to search for a mechanism to help it for creating new jobs and to spur the economy in order to face the foreign competition, fot this, we find the process of creating innovative entrepreneurial activity comes at the forefront of solutions for the purpose of achieving that. For the purpose of highlighting the role of this process and its future in the economy, this study seeks to consolidate the innovation’s concept and innovative entrepreneurship, then the success’s conditions of these entrepreneurships, to conclude with recommendations , solutions and important results.

Keywords: entrepreneurship, innovation, performance, vigilance, modernity, technology, business incubators

Procedia PDF Downloads 63

Authors: Ramesh P., Aby Joseph

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Micro Inverters provide Module Embedded Solution for harvesting energy from small-scale solar photovoltaic (PV) panels. In addition to higher modularity & reliability (25 years of life), the MicroInverter has inherent advantages such as avoidance of long DC cables, eliminates module mismatch losses, minimizes partial shading effect, improves safety and flexibility in installations etc. Due to the above-stated benefits, the renewable energy technology with Solar Photovoltaic (PV) Micro Inverter becomes more widespread in Village Nano Grid application ensuring grid independence for rural communities and areas without access to electricity. While the primary objective of this paper is to discuss the problems related to rural electrification, this concept can also be extended to urban installation with grid connectivity. This work presents a comprehensive analysis of the power circuit design, control methodologies and prototyping of 300Wₚ Single Phase PV Micro Inverter. This paper investigates two different topologies for PV Micro Inverters, based on the first hand on Single Stage Flyback/ Forward PV Micro-Inverter configuration and the other hand on the Double stage configuration including DC-DC converter, H bridge DC-AC Inverter. This work covers Power Decoupling techniques to reduce the input filter capacitor size to buffer double line (100 Hz) ripple energy and eliminates the use of electrolytic capacitors. The propagation of the double line oscillation reflected back to PV module will affect the Maximum Power Point Tracking (MPPT) performance. Also, the grid current will be distorted. To mitigate this issue, an independent MPPT control algorithm is developed in this work to reject the propagation of this double line ripple oscillation to PV side to improve the MPPT performance and grid side to improve current quality. Here, the power hardware topology accepts wide input voltage variation and consists of suitably rated MOSFET switches, Galvanically Isolated gate drivers, high-frequency magnetics and Film capacitors with a long lifespan. The digital controller hardware platform inbuilt with the external peripheral interface is developed using floating point microcontroller TMS320F2806x from Texas Instruments. The firmware governing the operation of the PV Micro Inverter is written in C language and was developed using code composer studio Integrated Development Environment (IDE). In this work, the prototype hardware for the Single Phase Photovoltaic Micro Inverter with Double stage configuration was developed and the comparative analysis between the above mentioned configurations with experimental results will be presented.

Keywords: double line oscillation, micro inverter, MPPT, nano grid, power decoupling

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Authors: Marina Shakleina, Konstantin Shaklein, Stanislav Yakiro

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The digitalization of modern human life over the last decade has facilitated the acquisition, storage, and processing of data, which are used to detect changes in consumer preferences and to improve the internal efficiency of the production process. This emerging trend has attracted academic interest in the use of big data in research. The study focuses on modeling the social comfort of the Russian population for the period 2010-2021 using big data. Big data provides enormous opportunities for understanding human interactions at the scale of society with plenty of space and time dynamics. One of the most popular big data sources is Google Trends. The methodology for assessing social comfort using big data involves several steps: 1. 574 words were selected based on the Harvard IV-4 Dictionary adjusted to fit the reality of everyday Russian life. The set of keywords was further cleansed by excluding queries consisting of verbs and words with several lexical meanings. 2. Search queries were processed to ensure comparability of results: the transformation of data to a 10-point scale, elimination of popularity peaks, detrending, and deseasoning. The proposed methodology for keyword search and Google Trends processing was implemented in the form of a script in the Python programming language. 3. Block and summary integral indicators of social comfort were constructed using the first modified principal component resulting in weighting coefficients values of block components. According to the study, social comfort is described by 12 blocks: ‘health’, ‘education’, ‘social support’, ‘financial situation’, ‘employment’, ‘housing’, ‘ethical norms’, ‘security’, ‘political stability’, ‘leisure’, ‘environment’, ‘infrastructure’. According to the model, the summary integral indicator increased by 54% and was 4.631 points; the average annual rate was 3.6%, which is higher than the rate of economic growth by 2.7 p.p. The value of the indicator describing social comfort in Russia is determined by 26% by ‘social support’, 24% by ‘education’, 12% by ‘infrastructure’, 10% by ‘leisure’, and the remaining 28% by others. Among 25% of the most popular searches, 85% are of negative nature and are mainly related to the blocks ‘security’, ‘political stability’, ‘health’, for example, ‘crime rate’, ‘vulnerability’. Among the 25% most unpopular queries, 99% of the queries were positive and mostly related to the blocks ‘ethical norms’, ‘education’, ‘employment’, for example, ‘social package’, ‘recycling’. In conclusion, the introduction of the latent category ‘social comfort’ into the scientific vocabulary deepens the theory of the quality of life of the population in terms of the study of the involvement of an individual in the society and expanding the subjective aspect of the measurements of various indicators. Integral assessment of social comfort demonstrates the overall picture of the development of the phenomenon over time and space and quantitatively evaluates ongoing socio-economic policy. The application of big data in the assessment of latent categories gives stable results, which opens up possibilities for their practical implementation.

Keywords: big data, Google trends, integral indicator, social comfort

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Authors: Veronica Diaz Quezada

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The society of the 21st century requires training of engineers capable of solving routine and non-routine problems in applications of the limit of real functions, as part of the course Calculus I. For this purpose, research was conducted with a methodological design that combines quantitative and qualitative procedures and that aims, to identify and to characterize the types of problems according to their nature and context, through the application of a mathematics test; to know— through a questionnaire— the opinion of difficulties in their solution, previous and missing knowledge of some students of three engineering careers of a state university in Chile. This research is completed with three case studies. The results favor the performance of students in solving problems of a fantasist and realistic context, but these do not guarantee mathematical skills which are necessary to solve non-routine problems of limit applications. In conclusion, through this research, it became clear that the students of the three engineerings do not have all the necessary skills to solve problems of application of the limit of a function of the real variable.

Keywords: case studies, engineering program, limits, problem solving

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Authors: Yi-Chun Chang, Ching-Ting Hsu, Wei-Hua Ho, Yueh-Tung Kuo

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Children with hearing impairment have deficits of balance and motors. Although most of parents teach deaf children communication skills in early life, but rarely teach the deficits of balance. The purpose of this study was to investigate whether static balance improved after table tennis training. Table tennis training was provided four times a week for eight weeks to two 12-year-old deaf children. The table tennis training included crossover footwork, sideway attack, backhand block-sideways-flutter forehand attack, and one-on-one tight training. Data were gathered weekly and statistical comparisons were made with a paired t-test. We observed that the dominant leg is better than the non-dominant leg in static balance and girl balance ability is better than boy. The final result shows that table tennis training significantly improves the deaf children’s static balance performance. It indicates that table tennis training on deaf children helps the static balance ability.

Keywords: deaf children, static balance, table tennis, vestibular structure

Procedia PDF Downloads 405

Authors: Phalaunnnaphat Siriwongs

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The classroom of the 21st century is an ever changing forum for new and innovative thoughts and ideas. With increasing technology and opportunity, students have rapid access to information that only decades ago would have taken weeks to obtain. Unfortunately, new techniques and technology are not the cure for the fundamental problems that have plagued the classroom ever since education was established. Class size has been an issue long debated in academia. While it is difficult to pin point an exact number, it is clear that in this case more does not mean better. By looking into the success and pitfalls of classroom size the true advantages of smaller classes will become clear. Previously, one class was comprised of 50 students. Being seventeen and eighteen- year- old students, sometimes it was quite difficult for them to stay focused. To help them understand and gain much knowledge, a researcher introduced “The Theory of Multiple Intelligence” and this, in fact, enabled students to learn according to their own learning preferences no matter how they were being taught. In this lesson, the researcher designed a cycle of learning activities involving all intelligences so that everyone had equal opportunities to learn.

Keywords: multiple intelligences, role play, performance assessment, formative assessment

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Authors: Hamed Saremi, Shahla Saremi

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In today's competitive world, organizations are expected to surpass the competitors and benefit from the resources and benefits. Therefore, organizations need to improve the current performance is felt more than ever that this requires to identify organizational optimal strategies, and consider all strategies simultaneously. In this study, to enhance competitive advantage and according to customer requirements, alignment between business, production and marketing strategies, House of Quality (QFD) approach has been used and zero-one linear programming model has been studied. First, the alignment between production and marketing strategies with business strategy, independent weights of these strategies is calculated. Then with using QFD approach the aligned weights of optimal strategies in each production and marketing field will be obtained and finally the aligned marketing strategies selection with the purpose of allocating budget and specialist human resource to marketing functions will be done that lead to increasing competitive advantage and benefit.

Keywords: marketing strategy, business strategy, strategy alignment, house of quality deployment, production strategy

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Authors: Hyung-Joon Kim, Jin-Young Park

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Energy dissipating devices (EDDs) have become more popular as seismic-force-resisting systems for building structures. However, there is little information on the collapse capacities of frames employing EDDs which are an important criterion for their seismic design. This study investigates the collapse capacities of steel frames with TADAS hysteric energy dissipative devices (HEDDs) that become an alternative to steel braced frames. To do this, 5-story steel ordinary concentrically braced frame and steel frame with HEDDs are designed and modeled. Nonlinear dynamic analyses and incremental dynamic analysis with 40 ground motions scaled to maximum considered earthquake are carried out. It is shown from analysis results that the significant enhancement in terms of the collapse capacities is found due to the introduction HEDDs.

Keywords: collapse capacity, incremental dynamic analysis, steel braced frame, TADAS hysteric energy dissipative device

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Authors: Hakim S. Sultan Aljibori

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An experimental procedure is developed to study the performance of composite thin wall cylinders subjected to internal pressure loading for investigations of stress distribution through the composite cylinders wall. Three types of fibers were used in this study are; woven roving glass fiber/epoxy, hybrid fiber/epoxy, and Kevlar fiber/epoxy composite specimens were fabricated and tested. All of these specimens subjected to uniformed pressure load using the hydraulic pump. Axial stress is identified, and values were found after collecting all the results. Comparison between the deferent types of specimens was done. Thus, the present investigation concludes the efficient and effective composite cylinder experimentally and provides a considerable advantage for using woven roving fibers in pressure vessels applications.

Keywords: stress distribution, composite material, internal pressure, glass fiber, hybrid fiber

Procedia PDF Downloads 141

Authors: M. Amo, A. Alvaro, A. Astudillo, R. Mc Culloch, J. C. del Castillo, M. Gómez, J. M. Martín

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Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) of course comprise a range of highly toxic compounds that may exist as particulates within the air or accumulate within water supplies, soil, or vegetation. They may be created either ubiquitously or naturally within the environment as a product of forest fires or volcanic eruptions. It is only since the industrial revolution, however, that it has become necessary to closely monitor their generation as a byproduct of manufacturing/combustion processes, in an effort to mitigate widespread contamination events. Of course, the environmental concentrations of these toxins are expected to be extremely low, therefore highly sensitive and accurate methods are required for their determination. Since ionization of non-polar compounds through electrospray and APCI is difficult and inefficient, we evaluate the performance of a novel low-flow Atmospheric Pressure Photoionization (APPI) source for the trace detection of various dioxins and furans using rapid Mass Spectrometry workflows. Air, soil and biota (vegetable matter) samples were collected monthly during one year from various locations within the vicinity of an industrial incinerator in Spain. Analytes were extracted and concentrated using soxhlet extraction in toluene and concentrated by rotavapor and nitrogen flow. Various ionization methods as electrospray (ES) and atmospheric pressure chemical ionization (APCI) were evaluated, however, only the low-flow APPI source was capable of providing the necessary performance, in terms of sensitivity, required for detecting all targeted analytes. In total, 10 analytes including 2,3,7,8-tetrachlorodibenzodioxin (TCDD) were detected and characterized using the APPI-MS method. Both PCDDs and PCFDs were detected most efficiently in negative ionization mode. The most abundant ion always corresponded to the loss of a chlorine and addition of an oxygen, yielding [M-Cl+O]- ions. MRM methods were created in order to provide selectivity for each analyte. No chromatographic separation was employed; however, matrix effects were determined to have a negligible impact on analyte signals. Triple Quadrupole Mass Spectrometry was chosen because of its unique potential for high sensitivity and selectivity. The mass spectrometer used was a Sciex´s Qtrap3200 working in negative Multi Reacting Monitoring Mode (MRM). Typically mass detection limits were determined to be near the 1-pg level. The APPI-MS2 technology applied to the detection of PCDD/Fs allows fast and reliable atmospheric analysis, minimizing considerably operational times and costs, with respect other technologies available. In addition, the limit of detection can be easily improved using a more sensitive mass spectrometer since the background in the analysis channel is very low. The APPI developed by SEADM allows polar and non-polar compounds ionization with high efficiency and repeatability.

Keywords: atmospheric pressure photoionization-mass spectrometry (APPI-MS), dioxin, furan, incinerator

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Authors: Olga Hernán-Vega, Patricia López-Rodríguez, David Escot-Bocanegra, Raúl Fernández-Recio, Ignacio Bravo

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Non-Cooperative Target Identification has become a key research domain in the Defense industry since it provides the ability to recognize targets at long distance and under any weather condition. High Resolution Range Profiles, one-dimensional radar images where the reflectivity of a target is projected onto the radar line of sight, are widely used for identification of flying targets. According to that, to face this problem, an approach to Non-Cooperative Target Identification based on the exploitation of Singular Value Decomposition to a matrix of range profiles is presented. Target Identification based on one-dimensional radar images compares a collection of profiles of a given target, namely test set, with the profiles included in a pre-loaded database, namely training set. The classification is improved by using Singular Value Decomposition since it allows to model each aircraft as a subspace and to accomplish recognition in a transformed domain where the main features are easier to extract hence, reducing unwanted information such as noise. Singular Value Decomposition permits to define a signal subspace which contain the highest percentage of the energy, and a noise subspace which will be discarded. This way, only the valuable information of each target is used in the recognition process. The identification algorithm is based on finding the target that minimizes the angle between subspaces and takes place in a transformed domain. Two metrics, F1 and F2, based on Singular Value Decomposition are accomplished in the identification process. In the case of F2, the angle is weighted, since the top vectors set the importance in the contribution to the formation of a target signal, on the contrary F1 simply shows the evolution of the unweighted angle. In order to have a wide database or radar signatures and evaluate the performance, range profiles are obtained through numerical simulation of seven civil aircraft at defined trajectories taken from an actual measurement. Taking into account the nature of the datasets, the main drawback of using simulated profiles instead of actual measured profiles is that the former implies an ideal identification scenario, since measured profiles suffer from noise, clutter and other unwanted information and simulated profiles don't. In this case, the test and training samples have similar nature and usually a similar high signal-to-noise ratio, so as to assess the feasibility of the approach, the addition of noise has been considered before the creation of the test set. The identification results applying the unweighted and weighted metrics are analysed for demonstrating which algorithm provides the best robustness against noise in an actual possible scenario. So as to confirm the validity of the methodology, identification experiments of profiles coming from electromagnetic simulations are conducted, revealing promising results. Considering the dissimilarities between the test and training sets when noise is added, the recognition performance has been improved when weighting is applied. Future experiments with larger sets are expected to be conducted with the aim of finally using actual profiles as test sets in a real hostile situation.

Keywords: HRRP, NCTI, simulated/synthetic database, SVD

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Authors: Balachandra Kumaraswamy, P. G. Poonacha

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Automatic Music Information Retrieval has been one of the challenging topics of research for a few decades now with several interesting approaches reported in the literature. In this paper we have developed a pitch extraction method based on a finite Fourier series approximation to the given window of samples. We then estimate pitch as the fundamental period of the finite Fourier series approximation to the given window of samples. This method uses analysis of the strength of harmonics present in the signal to reduce octave as well as harmonic errors. The performance of our method is compared with three best known methods for pitch extraction, namely, Yin, Windowed Special Normalization of the Auto-Correlation Function and Harmonic Product Spectrum methods of pitch extraction. Our study with artificially created signals as well as music files show that Fourier Approximation method gives much better estimate of pitch with less octave and harmonic errors.

Keywords: pitch, fourier series, yin, normalization of the auto- correlation function, harmonic product, mean square error

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Authors: Sumedha Weerasekara, Morgan Miles, Mark Morrison, Branka Krivokapic-Skoko

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This paper is aimed at exploring the interrelationships among entrepreneurial ecosystem factors and entrepreneurial cognition in regional and metropolitan ecosystems. Entrepreneurial ecosystem factors examined include: culture, infrastructure, access to finance, informal networks, support services, access to universities, and the depth and breadth of the talent pool. Using a multivariate approach we explore the impact of these ecosystem factors or elements on entrepreneurial cognition. In doing so, the existing body of knowledge from the literature on entrepreneurial ecosystem and cognition have been blended to explore the relationship between entrepreneurial ecosystem factors and cognition in a way not hitherto investigated. The concept of the entrepreneurial ecosystem has received increased attention as governments, universities and communities have started to recognize the potential of integrated policies, structures, programs and processes that foster entrepreneurship activities by supporting innovation, productivity and employment growth. The notion of entrepreneurial ecosystems has evolved and grown with the advancement of theoretical research and empirical studies. Importance of incorporating external factors like culture, political environment, and the economic environment within a single framework will enhance the capacity of examining the whole systems functionality to better understand the interaction of the entrepreneurial actors and factors within a single framework. The literature on clusters underplays the role of entrepreneurs and entrepreneurial management in creating and co-creating organizations, markets, and supporting ecosystems. Entrepreneurs are only one actor following a limited set of roles and dependent upon many other factors to thrive. As a consequence, entrepreneurs and relevant authorities should be aware of the other actors and factors with which they engage and rely, and make strategic choices to achieve both self and also collective objectives. The study uses stratified random sampling method to collect survey data from 12 different regions in regional and metropolitan regions of NSW, Australia. A questionnaire was administered online among 512 Small and medium enterprise owners operating their business in selected 12 regions in NSW, Australia. Data were analyzed using descriptive analyzing techniques and partial least squares - structural equation modeling. The findings show that even though there is a significant relationship between each and every entrepreneurial ecosystem factors, there is a weak relationship between most entrepreneurial ecosystem factors and entrepreneurial cognition. In the metropolitan context, the availability of finance and informal networks have the largest impact on entrepreneurial cognition while culture, infrastructure, and support services having the smallest impact and the talent pool and universities having a moderate impact on entrepreneurial cognition. Interestingly, in a regional context, culture, availability of finance, and the talent pool have the highest impact on entrepreneurial cognition, while informal networks having the smallest impact and the remaining factors – infrastructure, universities, and support services have a moderate impact on entrepreneurial cognition. These findings suggest the need for a location-specific strategy for supporting the development of entrepreneurial cognition.

Keywords: academic achievement, colour response card, feedback

Procedia PDF Downloads 129

Authors: Kazuki Kohama, Hiroko Ono

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The rainfall in Japan is gradually increasing every year according to Japan Meteorological Agency and Intergovernmental Panel on Climate Change Fifth Assessment Report. It means that the rainfall difference between rainy season and non-rainfall is increasing. In addition, the increasing trend of strong rain for a short time clearly appears. In recent years, natural disasters have caused enormous human injuries in various parts of Japan. Regarding water disaster, local heavy rain and floods of large rivers occur frequently, and it was decided on a policy to promote hard and soft sides as emergency disaster prevention measures with water disaster prevention awareness social reconstruction vision. Okinawa prefecture in subtropical region has torrential rain and water disaster several times a year such as river flood, in which is caused in specific rivers from all 97 rivers. Also, the shortage of capacity and narrow width are characteristic of river in Okinawa and easily cause river flood in heavy rain. This study focuses on Kohatu River that is one of the specific rivers. In fact, the water level greatly rises over the river levee almost once a year but non-damage of buildings around. On the other hand in some case, the water level reaches to ground floor height of house and has happed nine times until today. The purpose of this research is to figure out relationship between precipitation, surface outflow and total treatment water quantity of Kohatu River. For the purpose, we perform hydrological analysis although is complicated and needs specific details or data so that, the method is mainly using Geographic Information System software and outflow analysis system. At first, we extract watershed and then divided to 23 catchment areas to understand how much surface outflow flows to runoff point in each 10 minutes. On second, we create Unit Hydrograph indicating the area of surface outflow with flow area and time. This index shows the maximum amount of surface outflow at 2400 to 3000 seconds. Lastly, we compare an estimated value from Unit Hydrograph to a measured value. However, we found that measure value is usually lower than measured value because of evaporation and transpiration. In this study, hydrograph analysis was performed using GIS software and outflow analysis system. Based on these, we could clarify the flood time and amount of surface outflow.

Keywords: disaster prevention, water disaster, river flood, GIS software

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Authors: Seyed Abolhasan Naeini, Saeideh Mohammadi

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Embankment settlement on soft clays has always been problematic due to the high compaction and low shear strength of the soil. Deep soil mixing and geosynthetics are two soil improvement methods in such fields. Here, a numerical study is conducted on the embankment performance on the soft ground improved by deep soil mixing columns and geosynthetics based on the data of a real project. For this purpose, the finite element method is used in the Plaxis 2D software. The Soft Soil Creep model considers the creep phenomenon in the soft clay layer while the Mohr-Columb model simulates other soil layers. Results are verified using the data of an experimental embankment built on deep mixing columns. The effect of depth and diameter of deep mixing columns and the stiffness of geogrid on the vertical and horizontal movements of embankment on clay subsoil will be investigated in the following.

Keywords: PLAXIS 2D, embankment settlement, horizontal movement, deep soil mixing column, geogrid

Procedia PDF Downloads 155

Authors: Cristina Vatamanu, Doina Cosovan, Dragos Gavrilut, Henri Luchian

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In the past few years, the amount of malicious software increased exponentially and, therefore, machine learning algorithms became instrumental in identifying clean and malware files through semi-automated classification. When working with very large datasets, the major challenge is to reach both a very high malware detection rate and a very low false positive rate. Another challenge is to minimize the time needed for the machine learning algorithm to do so. This paper presents a comparative study between different machine learning techniques such as linear classifiers, ensembles, decision trees or various hybrids thereof. The training dataset consists of approximately 2 million clean files and 200.000 infected files, which is a realistic quantitative mixture. The paper investigates the above mentioned methods with respect to both their performance (detection rate and false positive rate) and their practicability.

Keywords: ensembles, false positives, feature selection, one side class algorithm

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Authors: Randa Boukhris, Alima Damak, Dorra Sellami

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Fingervein biometric authentication is one of the most popular and accurate technologies. However, low cost embedded solution is still an open problem. In this paper, a real-time implementation of fingervein recognition process embedded in Raspberry-Pi has been proposed. The use of Raspberry-Pi reduces overall system cost and size while allowing an easy user interface. Implementation of a target technology has guided to opt some specific parallel and simple processing algorithms. In the proposed system, we use four structural directional kernel elements for filtering finger vein images. Then, a Top-Hat and Bottom-Hat kernel filters are used to enhance the visibility and the appearance of venous images. For feature extraction step, a simple Local Directional Code (LDC) descriptor is applied. The proposed system presents an Error Equal Rate (EER) and Identification Rate (IR), respectively, equal to 0.02 and 98%. Furthermore, experimental results show that real-time operations have good performance.

Keywords: biometric, Bottom-Hat, Fingervein, LDC, Rasberry-Pi, ROI, Top-Hat

Procedia PDF Downloads 190

Authors: Qiu Chen, Koji Kotani, Feifei Lee, Tadahiro Ohmi

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In this paper, we propose an improved face recognition algorithm using histogram-based features in spatial and frequency domains. For adding spatial information of the face to improve recognition performance, a region-division (RD) method is utilized. The facial area is firstly divided into several regions, then feature vectors of each facial part are generated by Binary Vector Quantization (BVQ) histogram using DCT coefficients in low frequency domains, as well as Local Binary Pattern (LBP) histogram in spatial domain. Recognition results with different regions are first obtained separately and then fused by weighted averaging. Publicly available ORL database is used for the evaluation of our proposed algorithm, which is consisted of 40 subjects with 10 images per subject containing variations in lighting, posing, and expressions. It is demonstrated that face recognition using RD method can achieve much higher recognition rate.

Keywords: binary vector quantization (BVQ), DCT coefficients, face recognition, local binary patterns (LBP)

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Authors: D. Benatiallah, A. Benatiallah, K. Bouchouicha, A. Harouz

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The development and operation of renewable energy known an important development in the world with significant growth potential. Estimate the solar radiation on terrestrial geographic locality is of extreme importance, firstly to choose the appropriate site where to place solar systems (solar power plants for electricity generation, for example) and also for the design and performance analysis of any system using solar energy. In addition, solar radiation measurements are limited to a few areas only in Algeria. Thus, we use theoretical approaches to assess the solar radiation on a given location. The Adrar region is one of the most favorable sites for solar energy use with a medium flow that exceeds 7 kWh / m2 / d and saddle of over 3500 hours per year. Our goal in this work focuses on the creation of a data bank for the given data in the energy field of the Adrar region for the period of the year and the month then the integration of these data into a geographic Information System (GIS) to estimate the solar flux on a location on the map.

Keywords: Adrar, flow, GIS, deposit potential

Procedia PDF Downloads 349

Authors: O. M. Omar, A. M. Heniegal, G. D. Abd Elhameed, H. A. Mohamadien

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Local steel slag is produced as a by-product during the oxidation of steel pellets in an electric arc furnace. Using local steel slag waste as a hundred substitute of crushed stone in construction materials would resolve the environmental problems caused by the large-scale depletion of the natural sources of dolomite. This paper reports the experimental study to investigate the influence of a hundred replacement of dolomite as a coarse aggregate with local steel slag, on the fresh and hardened geopolymer concrete properties. The investigation includes traditional testing of hardening concrete, for selected mixes of cement and geopolymer concrete. It was found that local steel slag as a coarse aggregate enhanced the slump test of the fresh state of cement and geopolymer concretes. Nevertheless the unit weight of concretes was affected. Meanwhile, the good performance was observed when fly ash used as geopolymer concrete based.

Keywords: geopolymer, molarity, steel slag, sodium hydroxide, sodium silicate

Procedia PDF Downloads 289

Authors: F. R. M. Nascimento, E. E. S. Lora, J. C. E. Palácio

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A mathematical model to investigate the performance of a two stage fixed bed downdraft gasifier operating with air, steam and oxygen mixtures as the gasifying fluid has been developed. The various conditions of mixtures for a double stage fluid entry, have been performed. The model has been validated through a series of experimental tests performed by NEST – The Excellence Group in Thermal and Distributed Generation of the Federal University of Itajubá. Influence of mixtures are analyzed through the Steam to Biomass (SB), Equivalence Ratio (ER) and the Oxygen Concentration (OP) parameters in order to predict the best operating conditions to obtain adequate output gas quality, once is a key parameter for subsequent gas processing in the synthesis of biofuels, heat and electricity generation. Results show that there is an optimal combination in the steam and oxygen content of the gasifying fluid which allows the user find the best conditions to design and operate the equipment according to the desired application.

Keywords: air, equilibrium, downdraft, fixed bed gasification, mathematical modeling, mixtures, oxygen steam

Procedia PDF Downloads 465

Authors: Doyin Afolabi, Phillip Adewole, Oladipupo Sennaike

Abstract:

Most well-known classifiers, including the decision tree algorithm, can make predictions on balanced datasets efficiently. However, the decision tree algorithm tends to be biased towards imbalanced datasets because of the skewness of the distribution of such datasets. To overcome this problem, this study proposes a weighted decision tree algorithm that aims to remove the bias toward the majority class and prevents the reduction of majority observations in imbalance datasets classification. The proposed weighted decision tree algorithm was tested on three imbalanced datasets- cancer dataset, german credit dataset, and banknote dataset. The specificity, sensitivity, and accuracy metrics were used to evaluate the performance of the proposed decision tree algorithm on the datasets. The evaluation results show that for some of the weights of our proposed decision tree, the specificity, sensitivity, and accuracy metrics gave better results compared to that of the ID3 decision tree and decision tree induced with minority entropy for all three datasets.

Keywords: data mining, decision tree, classification, imbalance dataset

Procedia PDF Downloads 108

Authors: Amer Ait Sidhoum

Abstract:

Interest in sustainability has gained ground among practitioners, academics and policy-makers due to growing stakeholders’ awareness of environmental and social concerns. This is particularly true for agriculture. However, relatively little research has been conducted on the quantification of social sustainability and the contribution of social issues to the agricultural production efficiency. This research's main objective is to propose a method for evaluating prices of social outputs, more precisely shadow prices, by allowing for the stochastic nature of agricultural production that is to say for production uncertainty. In this article, the assessment of social outputs’ shadow prices is conducted within the methodological framework of nonparametric Data Envelopment Analysis (DEA). An output-oriented directional distance function (DDF) is implemented to represent the technology of a sample of Catalan arable crop farms and derive the efficiency scores the overall production technology of our sample is assumed to be the intersection of two different sub-technologies. The first sub-technology models the production of random desirable agricultural outputs, while the second sub-technology reflects the social outcomes from agricultural activities. Once a nonparametric production technology has been represented, the DDF primal approach can be used for efficiency measurement, while shadow prices are drawn from the dual representation of the DDF. Computing shadow prices is a method to assign an economic value to non-marketed social outcomes. Our research uses cross sectional, farm-level data collected in 2015 from a sample of 180 Catalan arable crop farms specialized in the production of cereals, oilseeds and protein (COP) crops. Our results suggest that our sample farms show high performance scores, from 85% for the bad state of nature to 88% for the normal and ideal crop growing conditions. This suggests that farm performance is increasing with an improvement in crop growth conditions. Results also show that average shadow prices of desirable state-contingent output and social outcomes for efficient and inefficient farms are positive, suggesting that the production of desirable marketable outputs and of non-marketable outputs makes a positive contribution to the farm production efficiency. Results also indicate that social outputs’ shadow prices are contingent upon the growing conditions. The shadow prices follow an upward trend as crop-growing conditions improve. This finding suggests that these efficient farms prefer to allocate more resources in the production of desirable outputs than of social outcomes. To our knowledge, this study represents the first attempt to compute shadow prices of social outcomes while accounting for the stochastic nature of the production technology. Our findings suggest that the decision-making process of the efficient farms in dealing with social issues are stochastic and strongly dependent on the growth conditions. This implies that policy-makers should adjust their instruments according to the stochastic environmental conditions. An optimal redistribution of rural development support, by increasing the public payment with the improvement in crop growth conditions, would likely enhance the effectiveness of public policies.

Keywords: data envelopment analysis, shadow prices, social sustainability, sustainable farming

Procedia PDF Downloads 106

Authors: Reuben Newell, Edward Archer, Alistair McIlhagger, Calvin Ralph

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Modern industry has developed a need for innovative 3D composite materials due to their attractive material properties. Composite materials are composed of a fibre reinforcement encased in a polymer matrix. The fibre reinforcement consists of warp, weft and binder yarns or tows woven together into a preform. The mechanical performance of composite material is largely controlled by the properties of the preform. As a result, the bulk of recent textile research has been focused on the design of high-strength preform architectures. Studies looking at optimisation of the weaving process have largely been neglected. It has been reported that yarns experience varying levels of damage during weaving, resulting in filament breakage and ultimately compromised composite mechanical performance. The weaving parameters involved in causing this yarn damage are not fully understood. Recent studies indicate that poor yarn tension control may be an influencing factor. As tension is increased, the yarn-to-yarn and yarn-to-weaving-equipment interactions are heightened, maximising damage. The correlation between yarn tension variation and weaving damage severity has never been adequately researched or quantified. A novel study is needed which accesses the influence of tension variation on the mechanical properties of woven yarns. This study has looked to quantify the variation of yarn tension throughout weaving and sought to link the impact of tension to weaving damage. Multiple yarns were randomly selected, and their tension was measured across the creel and shedding stages of weaving, using a hand-held tension meter. Sections of the same yarn were subsequently cut from the loom machine and tensile tested. A comparison study was made between the tensile strength of pristine and tensioned yarns to determine the induced weaving damage. Yarns from bobbins at the rear of the creel were under the least amount of tension (0.5-2.0N) compared to yarns positioned at the front of the creel (1.5-3.5N). This increase in tension has been linked to the sharp turn in the yarn path between bobbins at the front of the creel and creel I-board. Creel yarns under the lower tension suffered a 3% loss of tensile strength, compared to 7% for the greater tensioned yarns. During shedding, the tension on the yarns was higher than in the creel. The upper shed yarns were exposed to a decreased tension (3.0-4.5N) compared to the lower shed yarns (4.0-5.5N). Shed yarns under the lower tension suffered a 10% loss of tensile strength, compared to 14% for the greater tensioned yarns. Interestingly, the most severely damaged yarn was exposed to both the largest creel and shedding tensions. This study confirms for the first time that yarns under a greater level of tension suffer an increased amount of weaving damage. Significant variation of yarn tension has been identified across the creel and shedding stages of weaving. This leads to a variance of mechanical properties across the woven preform and ultimately the final composite part. The outcome from this study highlights the need for optimised yarn tension control during preform manufacture to minimize yarn-induced weaving damage.

Keywords: optimisation of preform manufacture, tensile testing of damaged tows, variation of yarn weaving tension, weaving damage

Procedia PDF Downloads 212

Authors: M. Ciminello, I. Dimino, S. Ameduri, A. Concilio

Abstract:

Improving aircraft's efficiency is one of the key elements of Aeronautics. Modern aircraft possess many advanced functions, such as good transportation capability, high Mach number, high flight altitude, and increasing rate of climb. However, no aircraft has a possibility to reach all of this optimized performance in a single airframe configuration. The aircraft aerodynamic efficiency varies considerably depending on the specific mission and on environmental conditions within which the aircraft must operate. Structures that morph their shape in response to their surroundings may at first seem like the stuff of science fiction, but take a look at nature and lots of examples of plants and animals that adapt to their environment would arise. In order to ensure both the controllable and the static robustness of such complex structural systems, a monitoring network is aimed at verifying the effectiveness of the given control commands together with the elastic response. In order to achieve this kind of information, the use of FBG sensors network is, in this project, proposed. The sensor network is able to measure morphing structures shape which may show large, global displacements due to non-standard architectures and materials adopted. Chord -wise variations may allow setting and chasing the best layout as a function of the particular and transforming reference state, always targeting best aerodynamic performance. The reason why an optical sensor solution has been selected is that while keeping a few of the contraindication of the classical systems (like cabling, continuous deployment, and so on), fibre optic sensors may lead to a dramatic reduction of the wires mass and weight thanks to an extreme multiplexing capability. Furthermore, the use of the ‘light’ as ‘information carrier’, permits dealing with nimbler, non-shielded wires, and avoids any kind of interference with the on-board instrumentation. The FBG-based transducers, herein presented, aim at monitoring the actual shape of adaptive trailing edge. Compared to conventional systems, these transducers allow more fail-safe measurements, by taking advantage of a supporting structure, hosting FBG, whose properties may be tailored depending on the architectural requirements and structural constraints, acting as strain modulator. The direct strain may, in fact, be difficult because of the large deformations occurring in morphing elements. A modulation transducer is then necessary to keep the measured strain inside the allowed range. In this application, chord-wise transducer device is a cantilevered beam sliding trough the spars and copying the camber line of the ATE ribs. FBG sensors array position are dimensioned and integrated along the path. A theoretical model describing the system behavior is implemented. To validate the design, experiments are then carried out with the purpose of estimating the functions between rib rotation and measured strain.

Keywords: fiber optic sensor, morphing structures, strain sensor, shape reconstruction

Procedia PDF Downloads 313